481 resultados para Mining City
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Purpose–The aims of this paper are to demonstrate the application of Sen’s theory of well-being, the capability approach; to conceptualise the state of transportation disadvantage; and to underpin a theoretical sounds indicator selection process. Design/methodology/approach–This paper reviews and examines various measurement approaches of transportation disadvantage in order to select indicators and develop an innovative framework of urban transportation disadvantage. Originality/value–The paper provides further understanding of the state of transportation disadvantage from the capability approach perspective. In addition, building from this understanding, a validated and systematic framework is developed to select relevant indicators. Practical implications –The multi-indicator approach has a high tendency to double count for transportation disadvantage, increase the number of TDA population and only accounts each indicator for its individual effects. Instead, indicators that are identified based on a transportation disadvantage scenario will yield more accurate results. Keywords – transport disadvantage, the capability approach, accessibility, measuring urban transportation disadvantage, indicators selection Paper type – Academic Research Paper
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This paper examines Australian media representations of the male managers of two global mining corporations, Rio Tinto and BHP Billiton. These organizations are transnational (or multinational) corporations with assets and/or operations across national boundaries (Dunning and Lundan, 2008), and indeed their respective Chief Executive Officers, Tom Albanese and Marius Kloppers are two of the most economically (and arguably politically) powerful in the world overseeing 37 000 and 39 000 employees internationally. With a 2008 profit of US$15.962 billion and assets of US$ 75.889 Billion BHP Billiton is the world's largest mining company. In terms of its profits and assets Rio Tinto ranks fourth in the world, but with operations in six countries (mainly Canada and Australia) and a 2008 profit of US$10.3 billion it is also emblematic of the transnational in that its ‘budget is larger than that of all but a few nations’ (Giddens, 2003, p. 62).
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This session is titled TRANSFORM! Opportunities and Challenges of Digital Content for Creative Economy. Some of the key concepts for this session include: 1. City / Economy 2. Creativity 3. Digital content 4. Transformation All of us would agree that these terms describe pertinent characteristics of contemporary world, the epithet of which is the ‘network era.’ I was thinking about what I would like to discuss here and what you, leading experts in divergent fields, would be interested to hear about. As the keynote for this session and as one of the first speakers for the entire conference, I see my role as an initiator for imagination, the wilder the better, posing questions rather than answers. Also given the session title Transform!, I wish to change this slightly to Transforming People, Place, and Technology: Towards Re-creative City in an attempt to take us away a little from the usual image depicted by the given topic. Instead, I intend to sketch a more holistic picture by reflecting on and extrapolating the four key concepts from the urban informatics point of view. To do so, I use ‘city’ as the primary guiding concept for my talk rather than probably more expected ‘digital media’ or ‘creative economy.’ You may wonder what I mean by re-creative city. I will explain this in time by looking at the key concepts from these four respective angles: 1. Living city 2. Creative city 3. Re-‐creative city 4. Opportunities and Challenges to arrive at a speculative yet probable image of the city that we may aspire to transform our current cities into. First let us start by considering the ‘living city.’
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Introduction Among the many requirements of establishing community health, a healthy urban environment stands out as significant one. A healthy urban environment constantly changes and improves community well-being and expands community resources. The promotion efforts for such an environment, therefore, must include the creation of structures and processes that actively work to dismantle existing community inequalities. In general, these processes are hard to manage; therefore, they require reliable planning and decision support systems. Current and previous practices justify that the use of decision support systems in planning for healthy communities have significant impacts on the communities. These impacts include but are not limited to: increasing collaboration between stakeholders and the general public; improving the accuracy and quality of the decision making process; enhancing healthcare services; and improving data and information availability for health decision makers and service planners. Considering the above stated reasons, this study investigates the challenges and opportunities of planning for healthy communities with the specific aim of examining the effectiveness of participatory planning and decision systems in supporting the planning for such communities. Methods This study introduces a recently developed methodology, which is based on an online participatory decision support system. This new decision support system contributes to solve environmental and community health problems, and to plan for healthy communities. The system also provides a powerful and effective platform for stakeholders and interested members of the community to establish an empowered society and a transparent and participatory decision making environment. Results The paper discusses the preliminary findings from the literature review of this decision support system in a case study of Logan City, Queensland. Conclusion The paper concludes with future research directions and applicability of this decision support system in health service planning elsewhere.
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This chapter investigates the challenges and opportunities associated with planning for a competitive city. The chapter is based on the assumption that a healthy city is a fundamental prerequisite for a competitive city. Thus, it is critical to examine the local determinants of health and factor these into any planning efforts. The main focus of the chapter is on the role of e-health planning, by utilising web-based geographic decision support systems. The proposed novel decision support system would provide a powerful and effective platform for stakeholders to access essential data for decision-making purposes. The chapter also highlights the need for a comprehensive information framework to guide the process of planning for healthy cities. Additionally, it discusses the prospects and constraints of such an approach. In summary, this chapter outlines the potential insights of using information science-based framework and suggests practical planning methods, as part of a broader e-health approach for improving the health characteristics of competitive cities.
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Information Overload and Mismatch are two fundamental problems affecting the effectiveness of information filtering systems. Even though both term-based and patternbased approaches have been proposed to address the problems of overload and mismatch, neither of these approaches alone can provide a satisfactory solution to address these problems. This paper presents a novel two-stage information filtering model which combines the merits of term-based and pattern-based approaches to effectively filter sheer volume of information. In particular, the first filtering stage is supported by a novel rough analysis model which efficiently removes a large number of irrelevant documents, thereby addressing the overload problem. The second filtering stage is empowered by a semantically rich pattern taxonomy mining model which effectively fetches incoming documents according to the specific information needs of a user, thereby addressing the mismatch problem. The experimental results based on the RCV1 corpus show that the proposed twostage filtering model significantly outperforms the both termbased and pattern-based information filtering models.
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The study of the creative industries is not much more than a decade old. What makes it fascinating is that it is dealing with a rapidly evolving process, where a good deal of Schumpeterian ‘creative destruction’ – of old industries, business models, and some familiar cultural and creative pursuits – can already be observed. What happens next – and who will be the winner – is hard to predict. Furthermore, the creative industries encompass both large-scale ‘industry’ (media, publishing, digital applications) and individual creative talent; both economic and cultural values, and both global reach and local context. Thus, the challenge is to integrate ‘top-down’ policy and planning with ‘bottom-up’ experimentation and innovation. There is always the promise that this new creative ecology will provide some novel answers to problems of wealth-creation for emergent economies, new solutions to problems of intellectual emancipation for individuals, and sustainable development for that most intense incubator of creative ideas, the city.
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Advances in data mining have provided techniques for automatically discovering underlying knowledge and extracting useful information from large volumes of data. Data mining offers tools for quick discovery of relationships, patterns and knowledge in large complex databases. Application of data mining to manufacturing is relatively limited mainly because of complexity of manufacturing data. Growing self organizing map (GSOM) algorithm has been proven to be an efficient algorithm to analyze unsupervised DNA data. However, it produced unsatisfactory clustering when used on some large manufacturing data. In this paper a data mining methodology has been proposed using a GSOM tool which was developed using a modified GSOM algorithm. The proposed method is used to generate clusters for good and faulty products from a manufacturing dataset. The clustering quality (CQ) measure proposed in the paper is used to evaluate the performance of the cluster maps. The paper also proposed an automatic identification of variables to find the most probable causative factor(s) that discriminate between good and faulty product by quickly examining the historical manufacturing data. The proposed method offers the manufacturers to smoothen the production flow and improve the quality of the products. Simulation results on small and large manufacturing data show the effectiveness of the proposed method.
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This study used the Australian Environmental Health Risk Assessment Framework to assess the human health risk of dioxin exposure through foods for local residents in two wards of Bien Hoa City, Vietnam. These wards are known hot-spots for dioxin and a range of stakeholders from central government to local levels were involved in this process. Publications on dioxin characteristics and toxicity were reviewed and dioxin concentrations in local soil, mud, foods, milk and blood samples were used as data for this risk assessment. A food frequency survey of 400 randomly selected households in these wards was conducted to provide data for exposure assessment. Results showed that local residents who had consumed locally cultivated foods, especially fresh water fish and bottom-feeding fish, free-ranging chicken, duck, and beef were at a very high risk, with their daily dioxin intake far exceeding the tolerable daily intake recommended by the WHO. Based on the results of this assessment, a multifaceted risk management program was developed and has been recognized as the first public health program ever to have been implemented in Vietnam to reduce the risks of dioxin exposure at dioxin hot-spots.
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Many cities worldwide face the prospect of major transformation as the world moves towards a global information order. In this new era, urban economies are being radically altered by dynamic processes of economic and spatial restructuring. The result is the creation of ‘informational cities’ or its new and more popular name, ‘knowledge cities’. For the last two centuries, social production had been primarily understood and shaped by neo-classical economic thought that recognized only three factors of production: land, labor and capital. Knowledge, education, and intellectual capacity were secondary, if not incidental, factors. Human capital was assumed to be either embedded in labor or just one of numerous categories of capital. In the last decades, it has become apparent that knowledge is sufficiently important to deserve recognition as a fourth factor of production. Knowledge and information and the social and technological settings for their production and communication are now seen as keys to development and economic prosperity. The rise of knowledge-based opportunity has, in many cases, been accompanied by a concomitant decline in traditional industrial activity. The replacement of physical commodity production by more abstract forms of production (e.g. information, ideas, and knowledge) has, however paradoxically, reinforced the importance of central places and led to the formation of knowledge cities. Knowledge is produced, marketed and exchanged mainly in cities. Therefore, knowledge cities aim to assist decision-makers in making their cities compatible with the knowledge economy and thus able to compete with other cities. Knowledge cities enable their citizens to foster knowledge creation, knowledge exchange and innovation. They also encourage the continuous creation, sharing, evaluation, renewal and update of knowledge. To compete nationally and internationally, cities need knowledge infrastructures (e.g. universities, research and development institutes); a concentration of well-educated people; technological, mainly electronic, infrastructure; and connections to the global economy (e.g. international companies and finance institutions for trade and investment). Moreover, they must possess the people and things necessary for the production of knowledge and, as importantly, function as breeding grounds for talent and innovation. The economy of a knowledge city creates high value-added products using research, technology, and brainpower. Private and the public sectors value knowledge, spend money on its discovery and dissemination and, ultimately, harness it to create goods and services. Although many cities call themselves knowledge cities, currently, only a few cities around the world (e.g., Barcelona, Delft, Dublin, Montreal, Munich, and Stockholm) have earned that label. Many other cities aspire to the status of knowledge city through urban development programs that target knowledge-based urban development. Examples include Copenhagen, Dubai, Manchester, Melbourne, Monterrey, Singapore, and Shanghai. Knowledge-Based Urban Development To date, the development of most knowledge cities has proceeded organically as a dependent and derivative effect of global market forces. Urban and regional planning has responded slowly, and sometimes not at all, to the challenges and the opportunities of the knowledge city. That is changing, however. Knowledge-based urban development potentially brings both economic prosperity and a sustainable socio-spatial order. Its goal is to produce and circulate abstract work. The globalization of the world in the last decades of the twentieth century was a dialectical process. On one hand, as the tyranny of distance was eroded, economic networks of production and consumption were constituted at a global scale. At the same time, spatial proximity remained as important as ever, if not more so, for knowledge-based urban development. Mediated by information and communication technology, personal contact, and the medium of tacit knowledge, organizational and institutional interactions are still closely associated with spatial proximity. The clustering of knowledge production is essential for fostering innovation and wealth creation. The social benefits of knowledge-based urban development extend beyond aggregate economic growth. On the one hand is the possibility of a particularly resilient form of urban development secured in a network of connections anchored at local, national, and global coordinates. On the other hand, quality of place and life, defined by the level of public service (e.g. health and education) and by the conservation and development of the cultural, aesthetic and ecological values give cities their character and attract or repel the creative class of knowledge workers, is a prerequisite for successful knowledge-based urban development. The goal is a secure economy in a human setting: in short, smart growth or sustainable urban development.
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‘Knowledge’ is a resource, which relies on the past for a better future. In the 21st century, more than ever before, cities around the world depend on the knowledge of their citizens, their institutions and their firms and enterprises. The knowledge image, the human competence and the reputation of their public and private institutions and corporations profiles a city. It attracts investment, qualified labour and professionals, as well as students and researchers. And it creates local life spaces and professional milieus, which offer the quality of life to the citizens that are seeking to cope with the challenges of modern life in a competitive world. Integrating knowledge-based development in urban strategies and policies, beyond the provision of schools and locations for higher education, has become a new ambitious arena of city politics. Coming from theory to practice, and bringing together the manifold knowledge stakeholders in a city and preparing joint visions for the knowledge city is a new challenge for city managers, urban planners and leaders of the civic society . It requires visionary power, creativity, holistic thinking, the willingness to cooperate with all groups of the local civil society, and the capability to moderate communication processes to overcome conflicts and to develop joint action for a sustainable future.
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The airport city concept has been embraced by many airports of different scales and in varied ways around the world. Airports everywhere have diversified their landside revenues with non-aviation commercial and industrial development in order to increase revenues and spread risk in the notoriously volatile aviation market. As intermodal hubs in a connected, globalised world, airports have evolved from transportation nodes into multi-faceted business enterprises. They have assumed a critical role as ‘transactional’ spaces in the global economy (Gottdiener 2001).
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In the late 20th century, a value-shift began to influence political thinking, recognising the need for environmentally, socially and culturally sustainable resource development. This shift entailed moves away from thinking of nature and culture as separate entities - The former existing merely to serve the latter. Cultural landscape theory recognises 'nature' as at once both 'natural', and as a 'cultural' construct. As such it may offer a framework through which to progress in the quest for 'sustainable development'. This 2005 Masters thesis makes a contribution to that quest by asking whether contemporary developments in cultural landscape theory can contribute to rehabilitation strategies for Australian open-cut coal mining landscapes, an examplar resource development landscape. A thematic historial overview of landscape values and resource development in Australis post-1788, and a review of cultural landscape theory literature contribute to the formation of the theoretical framework: "reconnecting the interrupted landscape". The author then explores a possible application of this framework within the Australian open-cut coal mining landscape.
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The XML Document Mining track was launched for exploring two main ideas: (1) identifying key problems and new challenges of the emerging field of mining semi-structured documents, and (2) studying and assessing the potential of Machine Learning (ML) techniques for dealing with generic ML tasks in the structured domain, i.e., classification and clustering of semi-structured documents. This track has run for six editions during INEX 2005, 2006, 2007, 2008, 2009 and 2010. The first five editions have been summarized in previous editions and we focus here on the 2010 edition. INEX 2010 included two tasks in the XML Mining track: (1) unsupervised clustering task and (2) semi-supervised classification task where documents are organized in a graph. The clustering task requires the participants to group the documents into clusters without any knowledge of category labels using an unsupervised learning algorithm. On the other hand, the classification task requires the participants to label the documents in the dataset into known categories using a supervised learning algorithm and a training set. This report gives the details of clustering and classification tasks.
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Road safety is a major concern worldwide. Road safety will improve as road conditions and their effects on crashes are continually investigated. This paper proposes to use the capability of data mining to include the greater set of road variables for all available crashes with skid resistance values across the Queensland state main road network in order to understand the relationships among crash, traffic and road variables. This paper presents a data mining based methodology for the road asset management data to find out the various road properties that contribute unduly to crashes. The models demonstrate high levels of accuracy in predicting crashes in roads when various road properties are included. This paper presents the findings of these models to show the relationships among skid resistance, crashes, crash characteristics and other road characteristics such as seal type, seal age, road type, texture depth, lane count, pavement width, rutting, speed limit, traffic rates intersections, traffic signage and road design and so on.